Add return air damper verification for configuration with direct buil…

…ding pressure.

.github/workflows/docs.yml

@@ -1,5 +1,9 @@
 name: Docs
-on: [push, pull_request, workflow_dispatch]
+on:
+  push:
+    branches: [ develop ]
+  pull_request:
+    branches: [ '*' ]
 jobs:
   docs:
     runs-on: ubuntu-latest

.github/workflows/unit_tests.yml

@@ -1,6 +1,6 @@
 on:
   push:
-    branches: [ develop ]
+    branches: [ '*' ]
   pull_request:
     branches: [ '*' ]
 

src/library/G36ReturnAirDamperPositionForReturnFanDirectBuildingPressure.py

@@ -0,0 +1,69 @@
+"""
+G36 2021
+
+### Description
+
+Section 5.16.2.3
+
+### Verification Logic
+
+```
+if heating_output > 0
+    if abs(ra_p - max_ra_p) < ra_p_tol
+        pass
+    else
+        fail
+    end
+else if cooling_output > 0
+    if abs(ra_p - 0) < ra_p_tol
+        pass
+    else
+        fail
+    end
+else 0 < ra_p < max_ra_p
+    pass
+else
+    fail
+end
+```
+
+"""
+
+import pandas as pd
+from checklib import RuleCheckBase
+import numpy as np
+
+
+class G36ReturnAirDamperPositionForReturnFanAirflowTracking(RuleCheckBase):
+    points = [
+        "heating_output",
+        "cooling_output",
+        "ra_p",
+        "max_ra_p",
+        "ra_p_tol",
+    ]
+
+    def return_air_damper(self, data):
+        if data["heating_output"] > 0:
+            if abs(data["ra_p"] - data["max_ra_p"]) < data["ra_p_tol"]:
+                return True
+            else:
+                return False
+        elif data["cooling_output"] > 0:
+            if data["ra_p"] < data["ra_p_tol"]:
+                return True
+            else:
+                return False
+        elif 0 < data["ra_p"] < data["max_ra_p"]:
+            return True
+        else:
+            return False
+
+    def verify(self):
+        self.result = self.df.apply(lambda d: self.return_air_damper(d), axis=1)
+
+    def check_bool(self):
+        if len(self.result[self.result == False] > 0):
+            return False
+        else:
+            return True

src/library/__init__.py

@@ -14,6 +14,7 @@
 from .G36SimultaneousHeatingCooling import *
 from .G36ReturnAirDamperPositionForReliefDamperOrFan import *
 from .G36ReturnAirDamperPositionForReturnFanAirflowTracking import *
+from .G36ReturnAirDamperPositionForReturnFanDirectBuildingPressure import *
 from .G36ReliefAirDamperPositionForReturnFanAirflowTracking import *
 from .G36OutdoorAirDamperPositionForReliefDamperOrFan import *
 from .G36OutdoorAirDamperPositionForReturnFanAirflowTracking import *
@@ -39,6 +40,7 @@
     "G36SimultaneousHeatingCooling",
     "G36ReturnAirDamperPositionForReliefDamperOrFan",
     "G36ReturnAirDamperPositionForReturnFanAirflowTracking",
+    "G36ReturnAirDamperPositionForReturnFanDirectBuildingPressure",
     "G36ReliefAirDamperPositionForReturnFanAirflowTracking",
     "G36OutdoorAirDamperPositionForReliefDamperOrFan",
     "G36OutdoorAirDamperPositionForReturnFanAirflowTracking",

tests/TestG36ReturnAirDamperPositionForReturnFanDirectBuildingPressure.py

@@ -0,0 +1,40 @@
+import unittest, sys
+
+sys.path.append("./src")
+from lib_unit_test_runner import *
+
+import pandas as pd
+import numpy as np
+
+
+class TestG36ReturnAirDamperPositionForReturnFanAirflowTracking(unittest.TestCase):
+    def test_return_air_damper_position(self):
+        points = [
+            "heating_output",
+            "cooling_output",
+            "ra_p",
+            "max_ra_p",
+            "ra_p_tol",
+        ]
+        data = [
+            [1000, 0, 0.5, 1.0, 0.05],  # False
+            [1000, 0, 0.99, 1.0, 0.05],  # True
+            [0, 1000, 0.5, 1.0, 0.05],  # False
+            [0, 1000, 0.02, 1.0, 0.05],  # True
+            [0, 0, 1.0, 1.0, 0.05],  # False
+            [0, 0, 0, 1.0, 0.05],  # False
+            [0, 0, 0.5, 1.0, 0.05],  # True
+        ]
+
+        df = pd.DataFrame(data, columns=points)
+
+        verification_obj = run_test_verification_with_data(
+            "G36ReturnAirDamperPositionForReturnFanAirflowTracking", df
+        )
+
+        results = pd.Series(list(verification_obj.result))
+        expected_results = pd.Series([False, True, False, True, False, False, True])
+        self.assertTrue(results.equals(expected_results))
+
+        binary_result = verification_obj.check_bool()
+        self.assertFalse(binary_result)